• Train AI models by reviewing responses and delivering consistent, actionable feedback. • Review and analyze customer feedback on AI behavior; document and recommend corrective actions. • Own the customer experience of AI-driven interactions and recommend appropriate escalation paths. • Generate clear, natural, and conversational written content for AI training. • Collaborate with cross-functional teams to improve processes, content, and AI outcomes. • Proactively identify issues, suggest solutions, and drive continuous improvement.

Role Description This is a remote position. As AI Ops Technical Leader, you drive the intelligent transformation of operations support. This player-coach role combines hands-on technical delivery, team leadership, and AI architecture governance to achieve operational excellence. You apply deep technical expertise and strategic leadership to design, build, and evolve AI and data solutions that improve incident management, major incident response, problem management, change enablement, service desk support, observability, and overall operational resilience. What You'll Be Doing: - Hands-on Data & AI Solutions for Operations Support: - Lead and contribute to high-impact data and AI initiatives that improve operations support outcomes, including real-time incident enrichment, automated root-cause analysis, predictive alerting, ticket clustering and auto-triage, change risk scoring, knowledge mining, and intelligent runbooks. - Design and deliver scalable AI-enabled features embedded into operations support platforms such as ServiceNow, Jira Service Management, monitoring/observability tools, and ITSM systems. - Ensure all solutions meet strict operational SLAs for reliability, low latency, auditability, explainability, and zero-downtime deployment. - Stay up to date with emerging AIOps tools, research, and trends, and apply them to enhance operations support. - AIOps Tools & Platform Leadership: - Lead the architecture, development, and continuous improvement of internal AIOps platforms and reusable components supporting operations teams. - Integrate AIOps tools with ITSM systems, observability platforms (Prometheus, Grafana, ELK, Dynatrace, Splunk), ticketing systems, and automation frameworks. - Apply best practices in MLOps/AI Ops tailored to production environments: model monitoring, drift detection, automated roll back, performance checks, and cost optimization at scale. - AI Technical Leadership for Operations Support Initiatives: - Serve as the principal AI technical authority for operations support transformation programs across service operations, NOC, support desks, infrastructure operations, and reliability engineering. - Lead technical discussions, architecture reviews, proof of concepts, vendor evaluations, and solution selection involving AI for operations. - Identify, prioritize, and drive high-value AI use cases focused on reducing MTTR/MTTD, automating L1 triage, predicting major incidents, generating post-mortems, optimizing shift handovers, and enabling proactive operations. - Team & People Leadership: - Build, mentor, and lead a high-performing squad of AIOps specialists focused on measurable operations support improvements. - Foster a culture of experimentation, production-first thinking, and commitment to operational impact—reduced toil, faster resolution, and higher availability. - Provide technical coaching, conduct design/code reviews, and guide career development with emphasis on operations and support domain expertise. - Stakeholder & Cross-Functional Collaboration: - Work closely with operations support leaders, incident managers, service owners, reliability engineers, ITSM teams, infrastructure groups, and other stakeholders to align AI solutions with operational needs. - Collaborate deeply with DS&AI Competency teams to ensure high-quality, scalable, and sustainable AI delivery. Qualifications - Strong background in data engineering, AI/ML, or operations support technology, including technical leadership in operations, IT, or service environments. - Proven track record delivering production AI/ML/data solutions that improve MTTR, MTTD, availability, and ticket deflection. - Hands-on expertise with Python, Spark, Kafka, Airflow, cloud data platforms, PyTorch/TensorFlow, LLMs, and integrations with tools like ServiceNow, PagerDuty, Splunk, Datadog, Moogsoft, Big Panda, Databricks, and Azure/ADF. - Deep knowledge of AIOps practices including event correlation, anomaly detection, predictive analytics, automated actions, and GenAI for operations. - Experience designing, building, or enhancing AIOps and internal tooling platforms. - Familiarity with ITIL processes (incident, problem, change, service request, knowledge management). - Experience with GenAI/LLM applications for operations such as copilots, auto-remediation, knowledge search, and alert/incident summarization. - Proven ability to scale AIOps in large operations or NOC environments while balancing hands-on work with strategy. - Strong communication skills, able to translate complex AI concepts for operations teams and executives, focusing on action and automation to reduce operational toil. Benefits - Missing one or two of these qualifications? We still want to hear from you! - If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.

Role Description Microsoft Azure Data Practice is seeking a seasoned Lead Data Architect to drive the design, delivery, and scaling of next-generation Data & AI solutions on the Microsoft Azure platform. This role is pivotal in establishing TGS as the partner of choice for enterprise clients pursuing data strategy, modernization, and AI-led transformation, with a deep focus on Microsoft Fabric and Azure AI. The ideal candidate is a hands-on thought leader who blends deep architectural expertise with business acumen, working seamlessly across delivery, pre-sales, and practice-building motions. You will architect mission-critical data platforms, build rapid proofs of concept (POCs) that demonstrate the art of the possible, and shape a cross-cloud practice that advances Microsoft Azure alongside AWS, GCP, Snowflake, and Databricks engagements. Responsibilities: - Architect and deliver enterprise-grade Data & AI solutions on Microsoft Azure using Microsoft Fabric, OneLake, Azure Databricks, and ADLS. - Build rapid proofs of concept (POCs) that demonstrate Microsoft Fabric and Microsoft AI Foundry implementation and migration scenarios for target clients. - Design Power BI semantic models and analytics patterns (Direct Lake, Premium capacity) that deliver enterprise BI at scale. - Establish data governance, lineage, and security frameworks using Microsoft Purview across the Azure data estate. - Lead end-to-end architecture for mission-critical data platforms – covering ingestion, processing, governance, consumption, and AI/ML serving layers. - Drive migration strategies from legacy platforms and competitive clouds to Microsoft Fabric, Azure Synapse, and Azure Databricks. - Architect AI and machine learning solutions using Microsoft AI Foundry and Azure Machine Learning, including GenAI and RAG-based patterns. - Partner directly with sales to formulate and execute go-to-market strategy that positions TGS as the partner of choice for data strategy and migration initiatives. - Lead architectural discussions with client executives and enterprise architects to build confidence and ensure customer success on new builds and migrations. - Conduct deep-dive hands-on training sessions and Art-of-the-Possible workshops for clients and internal teams. - Maintain a direct line of sight into in-flight Azure Data & AI projects to ensure adherence to global standards and delivery excellence. - Capture and share Microsoft Azure best-practice knowledge across TGS’s AWS, GCP, Snowflake, and Databricks practices. - Create and own the charter for Data & AI / GenAI initiatives aligned to Cloud Service Provider best practices and industry recommendations. - Mentor senior architects and engineers; contribute reference architectures, accelerators, and reusable IP to the practice. - Represent TGS in executive briefings, Microsoft joint sell motions, and industry events. Qualifications - 15+ years of progressive experience in Data Architecture, Engineering, and Operations on mission-critical platforms. - Deep hands-on expertise with Microsoft Fabric and OneLake, including Lakehouse, Warehouse, and Direct Lake patterns. - Hands-on experience with Microsoft AI Foundry and Azure Machine Learning for building AI, ML, and GenAI solutions. - Strong experience with Azure Fabric, Azure Databricks, Azure Data Factory, and ADLS Gen2 at enterprise scale. - Proven expertise designing and delivering Microsoft Power BI solutions including semantic models and Premium capacity workloads. - Solid experience implementing Microsoft Purview for data governance, lineage, classification, and compliance. - Demonstrated leadership on modernization and migration programs from legacy on-prem / competitive clouds to Azure-native platforms. - Proven success in pre-sales and solutioning – shaping RFPs, estimates, and executive proposals for multi-million-dollar engagements. - Strong executive communication and facilitation skills; comfortable presenting to CxOs and leading client workshops. - Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred); relevant Microsoft certifications strongly preferred. Benefits - Medical, Dental, and Vision - Critical Illness, Accident, and Hospital - 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available - Life Insurance (Voluntary Life and AD&D for employee and dependents) - Short and Long-Term Disability - Health Spending Account (HSA) - Transportation Benefits - Employee Assistance Program - Time Off/Leave (PTO, Vacation or Sick Leave) Company Description

• Define and own Tempo’s company-wide AI strategy aligned to business goals and product roadmap • Identify high-impact use cases across planning, forecasting, resource management, and productivity • Translate emerging AI capabilities into clear product and platform opportunities • Act as a thought partner to executive leadership on AI investments and priorities • Partner closely with Product leadership to define and execute the AI roadmap across Tempo’s product suite • Drive development of intelligent features such as predictive insights, recommendations, and automation • Establish a scalable AI platform layer that supports multiple products and use cases • Ensure AI capabilities are practical, usable, and deliver measurable customer value • Build and lead a high-performing team across GenAI, Agents, machine learning, data science, and applied AI engineering • Define operating model, hiring strategy, and capability roadmap for AI at Tempo • Foster strong collaboration across Product, Engineering, Design, and Data teams • Elevate AI literacy across the organization • Partner with Data and Platform teams to ensure strong foundations for AI development • Drive strategy for data quality, governance, and model lifecycle management • Ensure scalable, secure, and cost-effective AI infrastructure • Establish best practices for ethical, secure, and compliant use of AI • Ensure customer trust through transparency, privacy, and responsible model usage • Stay ahead of regulatory and industry developments related to AI • Represent Tempo as an AI leader in the Atlassian ecosystem and broader SaaS space • Engage with customers, partners, and industry communities • Bring external perspective on trends, tools, and competitive landscape